Language, Culture, and Gender Bias in AI-Driven Educational Platforms: Implications for Inclusive STEM Classrooms in the Global South

Artificial Intelligence (AI) is reshaping educational practices worldwide, particularly in Science, Technology, Engineering, and Mathematics (STEM) education. AI‑driven platforms increasingly mediate how students access content, interact with teachers, and demonstrate learning. However, these tools operate through specific languages, cultural assumptions, and datasets that are often rooted in Global North, English-dominant contexts.This Research Topic examines how language, culture, and gender intersect in AI‑mediated STEM education, especially in the Global South. We ask how AI tools used in classrooms may reproduce linguistic hierarchies (e.g., English over indigenous and regional languages), embed cultural biases, and reinforce gendered exclusions, and how they might also be redesigned to support more inclusive and equitable learning environments.We invite contributions that address, among others, the following themes:Linguistic Bias and Multilingualism in AI-Based Educational Tools: How language choice (English, national, regional, or indigenous languages) in AI interfaces affects access and participation in STEM learning. Challenges and possibilities of integrating bilingual and multilingual practices into AI-supported classrooms.Cultural and Gendered Representations in AI-Generated Educational Content: Analysis of stereotypes, omissions, or biases in AI‑generated examples, visuals, or narratives used in STEM education. How girls and women from diverse social locations (caste, class, religion, rural/urban) experience these representations.Diversity, Equity, and Inclusion in AI-Mediated STEM Pedagogy: Classroom practices and instructional designs that leverage AI while attending to linguistic, cultural, and gender diversity. Case studies of culturally responsive and gender-sensitive STEM teaching using AI tools.Global South Perspectives on Language, Culture, and AI in Education: Empirical and theoretical work from India, South Asia, and other Global South contexts that foreground local epistemologies, indigenous languages, and feminist perspectives in AI‑enhanced education. Topic editors: Chayanika Uniyal, Dr Amna Mirza Source: https://www.frontiersin.org/research-topics/76631/language-culture-and-gender-bias-in-ai-driven-educational-platforms-implications-for-inclusive-stem-classrooms-in-the-global-south